The PhD research can be characterised as operational research, building models of an existing warehouse system and proposing new operational models to improve the existing system. Read more Read less

It will contribute to the operational research discipline as well as warehouse management field by developing new models to optimise picking operations, using the emerging technological solutions offered by picking robots or other applicable technologies.

The PhD research will aim to improve warehouse picking operations using intelligent robots, specifically, path planning of intelligent picking robots. To achieve this aim, the following key objectives are identified:

  • To investigate the current state of the art in using intelligent picking robots in academic and practical literature.
  • To evaluate existing robot path planning methods and algorithms and develop models that optimise robot path planning (academic).
  • To develop guidelines for businesses on how to use and implement intelligent picking robots (practical).

The successful applicant will be working one day per week, or, equivalently, 44 days per year for the Centre for Logistics, Procurement and Supply Chain Management. Some indicative work can be expressed as follows:

  • Supporting the MSc programmes the centre runs (e.g. attending the study tours, preparing learning and teaching materials, marking)
  • Supporting the ongoing research in the centre (e.g. contributing to literature review, data analysis, report writing, and presentation preparation)
  • Supporting social media and online presence of the centre (e.g. content generation, growing the network)

At a glance

  • Application deadline30 Jun 2019
  • Award type(s)PhD
  • Start dateAs soon as possible
  • Duration of award3 years
  • EligibilityUK, EU, Rest of World
  • Reference numberSOM0004


1st Supervisor: Professor Emel Aktas
2nd Supervisor: Dr Hendrik Reefke

Entry requirements

Applicants must have a minimum of a good postgraduate/undergraduate degree (2.1 or higher) in Logistics and Supply Chain Management, Industrial Engineering, Systems Engineering, or Applied Mathematics. The ideal candidate will have a background in Operational Research, having built mathematical models in their MSc or Undergraduate projects, although these do not have to be at large scale.

The applicant’s academic writing ability will be evaluated based on the proposal submitted. The proposal should have an initial literature review on path planning in warehouse and preliminary mathematical formulation. Programming experience in a scientific language (MATLAB, R, or Python) is a must. The candidate should demonstrate self-initiation and self-learning. The applicant has to satisfy the general requirements for a PhD at Cranfield (numerical reasoning and critical thinking tests and the interview) and have the necessary social skills to engage with stakeholders and to communicate their research to nontechnical audiences.


Sponsored by Cranfield School of Management, this fully-funded studentship will provide a bursary of up to £15,009 (tax free) plus course fees for three years.

Cranfield Doctoral Network

Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral Network. This network brings together both research students and staff, providing a platform for our researchers to share ideas and collaborate in a multi-disciplinary environment. It aims to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of social and networking opportunities.

How to apply

For further information please contact: 

Professor Emel Aktas
T: (0) 1234 750111 Ext: 2420

If you are eligible to apply for this studentship, please complete the online application form making sure to quote reference number SOM0004 within your application.